The purpose of this paper is to illustrate the importance of using structural results in dynamic programming algorithms. We consider the problem of approximating optimal strategies for the batch service of customers at a service station. Customers stochastically arrive at the station and wait to be served, incurring a waiting cost and a service cost. Service of customers is performed in groups ...

This paper considers the minimization of makespan in unrelated parallel batch processing machines scheduling problem with considering non-identical job size and dynamic ready time. The considered have different capacity speed. Each machine processes a number jobs as at same time so that machine’s is not exceeded. are equal to largest batch, respectively. In this paper, Mixed Integer Linear Prog...

We formulate the call admission control problem for a single link in an integrated service environment as a Markov Decision Problem. In principle , an optimal admission control policy can be computed using methods of Dynamic Programming. However, as the number of possible states of the underlying Markov Chain grows exponentially in the number of customer classes, Dynamic Programming algorithms ...

In this paper we propose a methodology to set prices of perishable items in the context of a retail chain with coordinated prices among its stores and compare its performance with actual practice in a real case study. We formulate a stochastic dynamic programming problem and develop heuristic solutions that approximate optimal solutions satisfactorily. To compare this methodology with current p...

Many applications generate and consume temporal data and retrieval of time series is a key processing step in many application domains. Dynamic time warping (DTW) distance between time series of size N and M is computed relying on a dynamic programming approach which creates and fills an N × M grid to search for an optimal warp path. Since this can be costly, various heuristics have been propos...

An important class of algorithms for constraint optimization searches for solutions guided by a heuristic evaluation function (bound) that can be computed using tree decomposition and dynamic programming. Recently, it has been shown that if only a few best solutions are needed, the cost of pre-processing can be avoided by interleaving dynamic programming with search. In this paper, we extend th...

Dynamic voltage and frequency scaling proves to be an efficient way of reducing energy consumption of servers. Energy savings are typically achieved by setting a well-chosen frequency during some program phases. However, determining suitable program phases and their associated optimal frequencies is a complex problem. Moreover, hardware is constrained by non negligible frequency transition late...

A mobile user is roaming in a zone composed of many cells in a cellular network system. When a call arrives, the system pages the user in these cells since the user never reports its location unless it leaves the zone. Each cell is associated with a positive value which is the probability that the user resides in this cell. A delay constraint requires the user to be found within a predetermined...

Intelligent industrial and mobile robots may be considered proven technology in structured environments. Teach programming and supervised learning methods permit solutions to a variety of applications. However, we believe that to extend the operation of these machines to more unstructured environments requires a new learning method. Both unsupervised learning and reinforcement learning are pote...